class_docstr: Dataset builder that allows building a dataset without defining a class.
code: def _generate_examples_tf_data(
      self, ds: tf.data.Dataset
  ) -> split_builder_lib.SplitGenerator:
      for i, example in enumerate(dataset_utils.as_numpy(ds)):
          yield i, example
  
imports: from __future__ import annotations
  from collections.abc import Iterable, Mapping
  import typing
  from typing import Any, Dict
  from absl import logging
  from etils import epath
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import dataset_info
  from tensorflow_datasets.core import dataset_utils
  from tensorflow_datasets.core import download
  from tensorflow_datasets.core import features
  from tensorflow_datasets.core import file_adapters
  from tensorflow_datasets.core import split_builder
  from tensorflow_datasets.core import splits
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import apache_beam
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 4 for calling the AdhocBuilder obj's underlying member method code with example usage: obj._generate_examples_tf_data(ds) without return types